{"id":"https://openalex.org/W4416247192","doi":"https://doi.org/10.48550/arxiv.2510.19574","title":"Can You Trust What You See? Alpha Channel No-Box Attacks on Video Object Detection","display_name":"Can You Trust What You See? Alpha Channel No-Box Attacks on Video Object Detection","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4416247192","doi":"https://doi.org/10.48550/arxiv.2510.19574"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2510.19574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.19574","pdf_url":"https://arxiv.org/pdf/2510.19574","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.19574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5105949595","display_name":"Ariana Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi, Ariana","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659606","display_name":"Ce Zhou","orcid":"https://orcid.org/0000-0002-3238-7444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Ce","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044098602","display_name":"Liyang Xiao","orcid":"https://orcid.org/0000-0003-4027-7701"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Liyang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5084076598","display_name":"Qiben Yan","orcid":"https://orcid.org/0000-0003-0551-2163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Qiben","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5105949595"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6949999928474426},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6549999713897705},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.652899980545044},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6001999974250793},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.5541999936103821},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.524399995803833},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4948999881744385},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47380000352859497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7124000191688538},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6949999928474426},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6549999713897705},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.652899980545044},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6001999974250793},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5841000080108643},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.5541999936103821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5439000129699707},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.524399995803833},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48660001158714294},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47380000352859497},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.428600013256073},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C64943373","wikidata":"https://www.wikidata.org/wiki/Q2651003","display_name":"Alpha (finance)","level":4,"score":0.31859999895095825},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.2825999855995178},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.19574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.19574","pdf_url":"https://arxiv.org/pdf/2510.19574","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.19574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.19574","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.19574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.19574","pdf_url":"https://arxiv.org/pdf/2510.19574","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4416247192.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"object":[1,63,104,154],"detection":[2],"models":[3],"are":[4],"increasingly":[5],"deployed":[6],"in":[7,33,39,47,91,182,198],"cyber-physical":[8],"systems":[9],"such":[10],"as":[11],"autonomous":[12],"vehicles":[13],"(AVs)":[14],"and":[15,117,134,137,146,159],"surveillance":[16],"platforms,":[17],"ensuring":[18],"their":[19],"security":[20],"against":[21],"adversarial":[22,31,60,199],"threats":[23],"is":[24],"essential.":[25],"While":[26],"prior":[27],"work":[28],"has":[29],"explored":[30],"attacks":[32,38],"the":[34,40,48,57,69,77,125,187,195],"image":[35],"domain,":[36],"those":[37],"video":[41,85,94,132],"domain":[42],"remain":[43],"largely":[44],"unexamined,":[45],"especially":[46],"no-box":[49,59],"setting.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54],"present":[55],"\u03b1-Cloak,":[56],"first":[58],"attack":[61,107,169],"on":[62,151],"detectors":[64],"that":[65,95,142,192],"operates":[66],"entirely":[67],"through":[68],"alpha":[70,78,128,196],"channel":[71,79,197],"of":[72],"RGBA":[73],"videos.":[74],"\u03b1-Cloak":[75,150],"exploits":[76],"to":[80,98,111],"fuse":[81],"a":[82,87,92,139,156,160,167,178],"malicious":[83],"target":[84],"with":[86],"benign":[88],"video,":[89],"resulting":[90],"fused":[93],"appears":[96],"innocuous":[97],"human":[99],"viewers":[100],"but":[101],"consistently":[102],"fools":[103],"detectors.":[105],"Our":[106,175],"requires":[108],"no":[109,119],"access":[110],"model":[112,164],"architecture,":[113],"parameters,":[114],"or":[115],"outputs,":[116],"introduces":[118],"perceptible":[120],"artifacts.":[121],"We":[122,148],"systematically":[123],"study":[124],"support":[126],"for":[127,190,194],"channels":[129],"across":[130,172],"common":[131],"formats":[133],"playback":[135],"applications,":[136],"design":[138],"fusion":[140],"algorithm":[141],"ensures":[143],"visual":[144],"stealth":[145],"compatibility.":[147],"evaluate":[149],"five":[152],"state-of-the-art":[153],"detectors,":[155],"vision-language":[157],"model,":[158],"multi-modal":[161],"large":[162],"language":[163],"(Gemini-2.0-Flash),":[165],"demonstrating":[166],"100%":[168],"success":[170],"rate":[171],"all":[173],"scenarios.":[174],"findings":[176],"reveal":[177],"previously":[179],"unexplored":[180],"vulnerability":[181],"video-based":[183],"perception":[184],"systems,":[185],"highlighting":[186],"urgent":[188],"need":[189],"defenses":[191],"account":[193],"settings.":[200]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-24T00:00:00"}
